Cost-Related Access Barriers, Medical Debt, and Dissatisfaction with Care Among Privately Insured Americans.

BACKGROUND: Understanding experiences with private important to improving the quality of health care coverage. OBJECTIVE: To examine the association of health with cost-related access barriers, medical debt, and dissatisfaction with care among privately insured Americans. DESIGN: We classified Americans with private insurance by self-reported health status into five groups (excellent, very good, good, fair, and poor health). We examined self-reported difficulty seeing a doctor due to costs, not taking medications due to costs, medical debt, and dissatisfaction with care among individuals with differing health status. We used logistic regression to examine the association of health status with individuals' experiences after accounting for baseline characteristics. The analysis was repeated among individuals with different forms of private insurance. Odds ratios were converted to risk ratios to improve ease of interpretation of the results. SETTING: Behavioral Risk Factor Surveillance System of Americans in 17 states RESULTS: The sample included 82,494 US adults with private insurance. Following adjustment, compared to individuals with excellent health those in very good health, good health, fair health, and poor health reported increasingly higher risks of difficulty seeing a doctor due to costs with risk ratios of 1.02 (95% CI 1.01, 1.03), 1.07 (95% CI 1.06, 1.08), 1.18 (95% CI 1.17, 1.20), and 1.29 (95% CI 1.27, 1.31), respectively. Compared to individuals with excellent health, those in very good health, good health, fair health, and poor health reported increasingly higher risks of not taking medication due to costs, outstanding medical debt, and dissatisfaction with care. Similar relationships were seen across individually purchased and employer-sponsored insurance. CONCLUSION: Cost-related access barriers, medical debt, and dissatisfaction with care were common among individuals with private insurance and most pronounced among those with fair and poor health who likely need and use their health insurance the most.

Receipt of preventive health services and current cannabis users.

Substance use is associated with greater barriers and reduced access to care. Little research, however, has examined the relationship between cannabis use and receipt of preventive health services. Using data from the 2017 Behavioral Risk Factor Surveillance System, we examined the association between current cannabis use and receipt of 12 preventive health services, adjusting for sociodemographic characteristics and access to care. In analyses that adjusted for sociodemographic factors and access to care, participants with current cannabis use had lower odds of being vaccinated for influenza (AOR = 0.67, 95% CI = 0.54-0.83) and higher odds of ever receiving HPV vaccination (AOR = 1.77, 95% CI = 1.06-2.96) and HIV screening (AOR = 2.34, 95% CI = 1.88-2.92) compared with those without cannabis use. Among the 12 preventive services examined, we found three differences in receipt of preventive services by cannabis use status. Cannabis use does not appear to be associated with significant underuse of preventive services.

Access to Care, Cost of Care, and Satisfaction With Care Among Adults With Private and Public Health Insurance in the US.

Importance: Contemporary data directly comparing experiences between individuals with public and private health insurance among the 5 major forms of coverage in the US are limited. Objective: To compare individual experiences related to access to care, costs of care, and reported satisfaction with care among the 5 major forms of health insurance coverage in the US. Design, Setting, and Participants: This survey study used data from the 2016-2018 Behavioral Risk Factor Surveillance System on 149 290 individuals residing in 17 states and the District of Columbia, representing the experiences of more than 61 million US adults. Exposure: Private (individually purchased and employer-sponsored coverage) or public health insurance (Medicare, Medicaid, and Veterans Health Administration [VHA] or military coverage). Main Outcomes and Measures: A pairwise multivariable analysis was performed, controlling for underlying health status of US adults covered by private and public health insurance plans, and responses to survey questions on access to care, costs of care, and reported satisfaction with care were compared. Estimates are weighted. Results: A total of 149 290 individuals responded to the survey (mean [SD] age, 50.7 [0.2] years; 52.8% female). Among the respondents, most were covered by private insurance (95 396 [63.9%]), followed by Medicare (35 531 [23.8%]), Medicaid (13 286 [8.9%]), and VHA or military (5074 [3.4%]) coverage. Among those with private insurance, most (117 939 [79.0%]) had employer-sponsored coverage. Compared with those covered by Medicare, individuals with employer-sponsored insurance were less likely to report having a personal physician (odds ratio [OR], 0.52; 95% CI, 0.48-0.57) and were more likely to report instability in insurance coverage (OR, 1.54; 95% CI, 1.30-1.83), difficulty seeing a physician because of costs (OR, 2.00; 95% CI, 1.77-2.27), not taking medication because of costs (OR, 1.44; 95% CI, 1.27-1.62), and having medical debt (OR, 2.92; 95% CI, 2.69-3.17). Compared with those covered by Medicare, individuals with employer-sponsored insurance were less satisfied with their care (OR, 0.60; 95% CI, 0.56-0.64). Compared with individuals covered by Medicaid, those with employer-sponsored insurance were more likely to report having medical debt (OR, 2.06; 95% CI, 1.83-2.32) and were less likely to report difficulty seeing a physician because of costs (OR, 0.83; 95% CI, 0.73-0.95) and not taking medications because of costs (OR, 0.78; 95% CI, 0.66-0.92). No difference in satisfaction with care (OR, 0.96; 95% CI, 0.87-1.06) was found between individuals with employer-sponsored private health insurance and those with Medicaid coverage. Conclusions and Relevance: In this survey study, individuals with private insurance were more likely to report poor access to care, higher costs of care, and less satisfaction with care compared with individuals covered by publicly sponsored insurance programs. These findings suggest that public health insurance options may provide more cost-effective care than private options.

Estimation tools for reducing the impact of sampling and nonresponse errors in dual-frame RDD telephone surveys.

We discuss alternative estimators of the population total given a dual-frame random-digit-dial (RDD) telephone survey in which samples are selected from landline and cell phone sampling frames. The estimators are subject to sampling and nonsampling errors. To reduce sampling variability when an optimum balance of landline and cell phone samples is not feasible, we develop an application of shrinkage estimation. We demonstrate the implications for survey weighting of a differential nonresponse mechanism by telephone status. We illustrate these ideas using data from the National Immunization Survey-Child, a large dual-frame RDD telephone survey sponsored by the Centers for Disease Control and Prevention and conducted to measure the vaccination status of American children aged 19 to 35 months.

Statistical Methodology of the National Immunization Survey, 2005-2014.

The National Immunization Survey (NIS) family of surveys includes NIS-Child, which monitors vaccination coverage for the U.S. population of children aged 19-35 months; NIS- Teen, which monitors vaccination coverage for the U.S. population of adolescents aged 13-17; and NIS-Flu, which monitors influenza vaccination coverage for the U.S. population of children aged 6 months through 17 years. This report describes the methods used in this family of surveys during the 2005-2014 period.

Quantifying bias in a health survey: modeling total survey error in the national immunization survey.

Random-digit-dial telephone surveys are experiencing both declining response rates and increasing under-coverage due to the prevalence of households that substitute a wireless telephone for their residential landline telephone. These changes increase the potential for bias in survey estimates and heighten the need for survey researchers to evaluate the sources and magnitudes of potential bias. We apply a Monte Carlo simulation-based approach to assess bias in the NIS, a land-line telephone survey of 19-35 month-old children used to obtain national vaccination coverage estimates. We develop a model describing the survey stages at which component nonsampling error may be introduced due to nonresponse and under-coverage. We use that model and components of error estimated in special studies to quantify the extent to which noncoverage and nonresponse may bias the vaccination coverage estimates obtained from the NIS and present a distribution of the total survey error. Results indicated that the total error followed a normal distribution with mean of 1.72 per cent(95 per cent CI: 1.71, 1.74 per cent) and final adjusted survey weights corrected for this error. Although small, the largest contributor to error in terms of magnitude was nonresponse of immunization providers. The total error was most sensitive to declines in coverage due to cell phone only households. These results indicate that, while response rates and coverage may be declining, total survey error is quite small. Since response rates have historically been used to proxy for total survey error, the finding that these rates do not accurately reflect bias is important for evaluation of survey data. Published in 2011 by John Wiley & Sons, Ltd.

Assessment of immunization registry databases as supplemental sources of data to improve ascertainment of vaccination coverage estimates in the national immunization survey.

OBJECTIVE: To evaluate the use of immunization registry data to supplement missing or incomplete vaccination data reported by immunization providers (referred to as "providers" hereafter) in the National Immunization Survey. DESIGN: Cross-sectional, random-digit-dialing, telephone survey to measure vaccination coverage among children aged 19 to 35 months in the United States. SETTING: Four sites with mature (with >67% of provider participation in the area) immunization registries. PARTICIPANTS: Of the 639 children with complete household interviews, interviewers had consent from the respondents for 569 (89.0%) children to contact their providers and for 556 (87.0%) children to contact both providers and registries. MAIN OUTCOME MEASURES: Percentages of children up-to-date for vaccines based on data from providers, registries, and both sources combined. RESULTS: According to provider-reported data, weighted estimates of coverage for the recommended childhood vaccine series 4:3:1:3 at the 4 sites were 65.6%, 78.8%, 81.6%, and 77.0%. According to registry data, these coverage rates were consistently lower: 31.7% (P<.05), 65.4%, 71.9%, and 61.8%, respectively. When all unique vaccine doses were combined from both sources, the pooled 4:3:1:3 coverage rates increased to 72.0%, 92.0%, 88.7%, and 80.2%, respectively. The quality and completeness of vaccination histories from the registries were inconsistent and varied by sites. CONCLUSIONS: Vaccination coverage estimates were the lowest when only registry-reported data were used and were the highest when provider- and registry-reported histories were combined. Although registries enrolled and matched more children, vaccination histories were missing, incomplete, and inconsistent. The quality and completeness of the registry data must be improved and must be comparable across all states before further consideration may be given to supplement or replace the provider-reported National Immunization Survey data.

Statistical methodology of the National Immunization Survey, 1994-2002.

OBJECTIVES: Since 1994 the National Immunization Survey (NIS) has monitored progress toward the Healthy People 2000 and 2010 vaccination goals. The NIS collects data in two phases: first, a random-digit-dialing (RDD) telephone survey to identify households with children 19-35 months old and, second, a mail survey to vaccination providers to obtain vaccination histories used to estimate vaccination coverage rates. This report reviews the methodologies used in the 1994-2002 NIS to obtain official estimates of vaccination coverage and describes the methodology used for the first three topical modules of the NIS. METHODS: From 1994 to 1997 the NIS used a variation of a two-phase estimator to compensate for missing provider-reported vaccination histories. Between 1998 and 2001 a weighting-class estimator was used. In 2002 and thereafter the weighting-class approach was refined to account for households that do not have telephones and for unvaccinated children. To collect data on immunization-related topics, the NIS sample was randomized among three topical modules: health insurance and ability to pay for vaccinations (HIM); parental knowledge and experiences about vaccinations (PKM); and daycare attendance, breastfeeding practices, and participation in the Special Supplemental Nutrition Program for Women, Infants, and Children (DCM). RESULTS: In 2001 among children with completed RDD interviews, 0.3 percent were entirely unvaccinated. Together, the new nontelephone adjustment and the refinement for unvaccinated children yielded revised estimates that were within 1.5 percentage points of the original estimates obtained using the 1998-2001 methodology. Over the six quarters during which the first three topical modules were fielded (from mid-2001 through 2002), 21,163 children were randomized to the HIM, 3576 to the PKM, and 3511 to the DCM.

Adjustments for non-telephone bias in random-digit-dialling surveys.

Telephone surveys are widely used in the U.S.A. for the study of health-related topics. They are subject to 'coverage bias' because they cannot sample households that do not have telephones. Although only around 5 per cent of households do not have a telephone, rates of telephone coverage show substantial variation by geography, demographic factors and socio-economic factors. In particular, lack of telephone service is more common among households that contain ethnic and racial minorities or that have lower socio-economic status with fewer opportunities for access to medical care and poorer health outcomes. Thus, failure to adequately account for households without telephones in health surveys may yield estimates of health outcomes that are misleading, particularly in states with at least moderate telephone non-coverage. The dynamic nature of the population of households without telephones offers a way of accounting for such households in telephone surveys. At any given time the population of telephone households includes households that have had a break or interruption in telephone service. Empirical results strongly suggest that these households are very similar to households that have never had telephone service. Thus, sampled households that report having had an interruption in telephone service may be used also to represent the portion of the population that has never had telephone service. This strategy can lead to a reduction in non-coverage bias in random-digit-dialling surveys. This paper presents two methods of adjusting for non-coverage of non-telephone households. The effectiveness of these methods is examined using data from the National Health Interview Survey. The interruption-in-telephone-service methods reduce non-coverage bias and can also result in a lower mean squared error. The application of the interruption-in-telephone-service methods to the National Immunization Survey is also discussed. This survey produces estimates for the 50 states and 28 urban areas. The interruption-in-telephone-service estimates tend be slightly lower than estimates resulting from poststratification and from another non-coverage adjustment method. The results suggest that the reduction in bias is greatest for variables that are highly correlated with the presence or absence of telephone service.